Dataset describing problem factors of partnering relationships in the Malaysian construction industry

The dataset indicates the problem factors which may influence the development of partnering relationship between two key project parties - the main contractor and the subcontractor. A total of 53 problem factors were identified and were clustered into five categories. An online questionnaire was used to elicit the viewpoints of these key parties with regards to the extent to which the factors have an impact on the partnering relationship in the Malaysian construction industry. The target respondents were managers and engineers of various construction companies in Malaysia with the main contractors or subcontractors who have projects in Kuala Lumpur, Shanghai and New Delhi. Both descriptive and quantitative analysis approaches were used to present the data. Relative Importance Index method was used to determine the top challenges to building favourable partnering relationships; and Partial Least Squares Structural-Equation Modelling (PLS-SEM) analysis was conducted to examine the role played by each cluster of factors in explaining the quality of partnering relationship between the main contractors and subcontractors. This data set would assist practitioners to work on the major problem factors to improve the quality of partnering relationship between the key participants in their present and future construction projects. By eliminating or minimizing these problem factors, practitioners will contribute significantly to effective supply chain management in the construction industry. The data would be of value to academics and industry professionals involved in the construction business domestically and internationally.


a b s t r a c t
The dataset indicates the problem factors which may influence the development of partnering relationship between two key project parties -the main contractor and the subcontractor. A total of 53 problem factors were identified and were clustered into five categories. An online questionnaire was used to elicit the viewpoints of these key parties with regards to the extent to which the factors have an impact on the partnering relationship in the Malaysian construction industry. The target respondents were managers and engineers of various construction companies in Malaysia with the main contractors or subcontractors who have projects in Kuala Lumpur, Shanghai and New Delhi. Both descriptive and quantitative analysis approaches were used to present the data. Relative Importance Index method was used to determine the top challenges to building favourable partnering relationships; and Partial Least Squares Structural-Equation Modelling (PLS-SEM) analysis was conducted to examine the role played by each cluster of factors in explaining the quality of partnering relationship between the main contractors and subcontractors. This data set would assist practitioners to work on the major problem factors to improve the quality of partnering relationship between the key participants in their present and future construction projects. By eliminating or minimizing these problem factors, practitioners will contribute significantly to effective supply chain management in the construction industry. The data would be of value to academics and industry professionals involved in the construction business domestically and internationally.
© 2022 The Author(s Value of the data • The data collected help to identify the problem factors leading to the adversarial relationships among the construction industry players as a result of conflicting interests in the supply chain. • The data will assist practitioners to focus on the major problem factors which have existed between participants in the construction industry in their present and future projects. • Specifically, the data indicate that problems related to the subcontractors (substandard quality of work and non-adherence to the conditions of the contract) negatively affect the main and subcontractor partnering relationship, which in turn, affects the performance of the construction projects. • The data imply that careful selection of subcontractors is important. Stringent selection of subcontractors and close monitoring of their performance are critical in enhancing successful project implementation with the aim of maximizing profit and minimizing risks.

Objective
Quality supply chain management practises are critical in the business industry [ 1 , 2 , 3 ]. However, few studies have examined the entirety of a partnered relationship from the perspectives of both sides especially in the construction industry. Furthermore, it is not addressed how problem elements and partnering relationships relate to the effective completion of building projects. The adoption of partnership relationships in supply chain management has been hampered by several discrepancies despite practitioners' realisation that these relationships must be longlasting and mutually beneficial. These inconsistencies are caused by a number of participantrelated issues. The dataset aims to reveal the participant-related issues in the construction industry.

Data description
The dataset [4] comprises of the problem factors leading to conflicts between two parties in the construction industry, specifically the problem factors impeding the development of partnering relationships. Fifty-three (53) problem factors were identified from the literature and were grouped into five categories: (1) factors related to the project owner, (2) factors related to the main contractor, (3) factors related to the subcontractor, (4) factors related to the consultant, and (5) factors related to the external environment. In addition, the dataset also presents the relationship indicator between contractor and subcontractor, which reflects the level of partnering or quality relationship between main contractor and subcontractor. Data were coded in Excel file format and processed via SmartPLS version 3.2.8. Table 1 presents the 53 problem factors by category as well as the relationship indicator. Pilot testing was also conducted and therefore MC21 and PO7 were excluded from the questionnaire for final data collection due to the low loading values. The data is described and tabulated from Tables 2 to 6 . Table 2 presents the profile of the respondents, which comprises the type of project, types of project owners, role of respondent, working experiences in construction sector, country of project located and project budget. Table 3 shows the top 10 problem factors relating to the main contractors and the subcontractors generated by using relative important index (RII) equation. There are 11 problem factors in this top 10 list due to the tie of two factors in rank 7. Five of these 11 problem factors are related to the main contractor and five are related to the subcontractor. Only one problem factor is related to the project owner. Table 4 presents the validity and reliability checking of the data. Factors with loadings of more than 0.70 were retained in the research model and those with less than 0.70 were deemed not reliable and hence, omitted. Cronbach's alpha values and composite reliability (CR) of the factors are all above 0.70 indicating that the items assigned to the respective constructs are reliable. The extracted average variances (AVEs) are all above 0.50 which shows that convergent validity is established in the measurement model [5] . Table 5 shows that the heterotrait-monotrait (HTMT) values are all less than 0.85 indicating that discriminant validity is also established (Hair et al., 2017). Table 6 presents the path coefficients of the model. The R-Square value of 0.246 shows that all the five independent variables, namely project consultant-related, main contractor-related, subcontractor-related, project owner-related, and environmental-related problem factors could explain about 25% of the variance in the partnering relationship. However, only the cluster of factors related to the subcontractor significantly affected the quality of the partnering relationship.  Gain and pain sharing was agreed between the parties RI3 A high degree of trust exist between parties RI4 Parties did not blame each other when problems occurred RI5 Both parties work jointly together RI6 Communication between the parties was open and effective RI7 The problem solving mechanism between the parties was effective RI8 Risk allocation between the parties was clear and fair RI9 Performance was reviewed and fed back on a regular basis RI10 Improvement was continuously made during the project

Experimental design, materials and methods
The research utilized a quantitative approach, in which a self-administered online questionnaire was developed to incorporate the problem factors affecting the quality of the partnering relationship between the main contractors and subcontractors. The problem factors were adopted from the framework of [6] . The measurement items used a five-point Likert scale with 1 = "strongly disagree" and 5 = "strongly agree". The questionnaire for this dataset is attached as a supplementary file. Questionnaire was distributed via Google Forms to the construction managers and engineers of project contractors and subcontractors in Kuala Lumpur, Shanghai and New Delhi. Before the online survey was conducted, the respondent was informed on the participation of the survey is based on voluntary basis. The Confidential Agreement was attached with the questionnaire when the questionnaire was distributed to the respondents. Purposive sampling was used as the questionnaire targeted project practitioners such as project managers, site managers, and engineers. A total of 144 completed questionnaires were received. However, 20 of these returned questionnaires were not usable as they were completed by non-target respondents, yielding the final sample size of 124. This sample size of 124 exceeded the minimum sample size of 92 generated from G * Power with the effect size of 0.15, significant level of 0.05, power of 0.80, and five predictors. Following the approach used by [6] , the Relative Importance Index method was used to rank the problem factors as perceived by the main contractors and  subcontractors. Partial Least Squares-Structural Equation Modelling (PLS-SEM) was used to check the convergent validity and discriminant validity of the data via measurement model assessment while structural model assessment was performed to verify the cluster of factors that plays a role in explaining the MC-SC partnering relationship.

Ethics statements
Before the commencement of the project, the Institutional Ethics Committee (IEC) of UCSI University had granted the approvals for the data collection (IEC-2022-FBM-081). The selfadministered survey was carried out in complete anonymity for the respondents. No sensitive or private data that could be used to identify the respondents was gathered. Before the online survey was conducted, the respondents' consent to participate in the survey was obtained.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data Availability
Dataset Describing Problem Factors of Partnering Relationships in the Malaysian Construction Industry (Original data) (Mendeley Data)